AS-821-16 Resolution on Procedures for Online Student Evaluation of Instruction

Sets official procedure for online student evaluation of instruction

Formative and Summative Assessment Techniques for Continuous Agricultural Technology Classroom Improvement

Four formative and summative learning assessment tools were used in two terms of an agricultural technology course. The formative assessment tools were a weekly e-mail feedback journal and a midterm electronic-survey. The summative assessment tools were a focus group and a student evaluation of instruction form administered at the end of each term. The weekly e-mail feedback journal and midterm e-survey assessments enabled several course adjustments during each course term, e.g., adjusting the content of the next class based on e-mail feedback, offering more real-world examples, and providing more example problems. The focus groups were used to explore more deeply students\u27 perceptions of both the course and the formative assessments. The student evaluation of instruction form did not provide as much useful information about student learning and course improvement as the other assessments. Using multiple formative and summative classroom assessment techniques for a course had a synergistic effect on gaining insights into the teaching-learning process

An analysis (between and within classrooms) of student evaluation of instruction

Much of the previous research on student ratings of their teachers has used inappropriate methods of analysis. These analyses fail to recognize that the score a student gives his instructor may depend upon characteristics of that student as well as upon the characteristics and behaviors of the instructor;The data of this study consisted of 2,107 students enrolled in several sections of 30 courses, resulting in 88 classrooms. The methodology used in this study analyzes student variability within classrooms separately from one classroom to another and incorporates the fact that results from these two kinds of analysis are expected to be the same if teacher and students do not differ from one classroom to another. It also recognizes that when student characteristics are related to how those students rate their instructors, and classrooms have different kinds of students in them, relative to these characteristics, then the ratings received by instructors are not comparable because student differences are confounded with teacher differences;Factor analysis of the between correlations results in 10 factors. These same factors tended to occur in the within analysis, but the within classroom variability was substantially smaller than the between classroom variability, indicating differences in the ratings received by different instructors. Within classrooms, females tended to rate their instructors slightly higher than did males (r (TURNEQ) .05), but this correlation was substantially larger (r (TURNEQ) .4) for the between analysis suggesting that courses preferred by females (e.g., home economics courses) are rated higher than courses preferred by males (e.g., engineering courses). Also, those classrooms with students who anticipated high grades, and who took the course as an elective tended to be rated higher than classrooms with students with other characteristics. These relationships were smaller or nonexistent within classrooms. Self-reported GPA was negatively related to the student rating of the textbook for the between analysis, and essentially unrelated to the other nine variables; otherwise, for these eighty classrooms which vary in both content and level, it appears that student characteristics play a substantial role in determining the average rating and suggests that ratings of teachers are comparable only to the extent that the students who rate those teachers have similar characteristics

Web and Paper SEI Reports by Calendar Year

This document contains tables comparing new web-based Student Evaluation of Instruction (SEI) to paper SEIs

Continuous Engineering Course Improvement through Synergistic use of Multiple Assessment

During two terms of a fluid power engineering course, four formative and summative course assessments, weekly e-mail feedback journals, midterm e-surveys, focus groups, and departmental student evaluation of instruction (SEI) forms, were used to assess student perceptions of their learning and the instruction methods used. The weekly e-mail feedback journals and midterm e-surveys enabled several course adjustments during each course term. Focus groups were used to explore students\u27 perceptions of both the course and the formative assessments. The SEI provided quantitative measures of student satisfaction that correlated with the focus group discussions. Using multiple formative and summative course assessments techniques had a synergistic effect on gaining insights into the teaching-learning process

The Relationship Between Student Evaluation of Instruction and Selected Predictors

The study attempted to determine the relationship between student evaluation of instruction and institutional performance ratings with the following predictors: faculty job satisfaction, faculty attitudes toward the evaluation process, faculty attitudes toward factors associated with the evaluation process, and faculty characteristics

Students’ comments about university teaching: which links with effectiveness models?

Se presentan los resultados de un análisis temático de contenido sobre 550 comentarios dentro un proceso de evaluación instruccional en estudiantes de la Universidad de Mons. Se buscan vínculos entre las características del profesor eficaz según los estudiantes y una revisión de la literatura científica, contemplando, en primer lugar, la enseñanza efectiva en la educación primaria y secundaria, y en segundo lugar, se expone la valoración de las instrucciones acerca de los profesores en la educación superior. Los resultados informan de una relación entre los comentarios de los estudiantes y las instrucciones docentes, y que la gestión de aula del profesor dobla en dos veces a sus características personales (por ejemplo, sentido del humor).  Aquest treball presenta els resultats d'una anàlisi temàtica de contingut sobre 550 comentaris realitzats per estudiants, com a part d'un procés d'avaluacióinstruccional amb estudiants de la Universitat de Mons. Es persegueix establir un vincle entre les principals característiques del professor eficaç vistes pels estudiants i una revisió de la literatura científica contemplant, en primer lloc, l'ensenyament efectiu en l'educació primària i en la secundària, per a passar en segon lloc, a exposar la valoració dels estudiants sobre les instruccions dels seus professors en l'educació superior. Els resultats informen d'una relació entre els comentaris dels estudiants i les instruccions docents, i que la gestió d'aula del professor doblega en dues vegades a les seues característiques personals (per exemple, sentit de l'humor).This article presents the results of the thematic content analysis of 550 comments written by students as part of the student evaluation of instruction at the University of Mons. It also seeks to establish a link between the characteristics of the effective teacher as seen by students and a review of the literature on, firstly, effective teaching at the primary and secondary education, and secondly, student evaluation of instruction in higher education. The results indicate that students’ comments relate to the teacher’s instruction and class management twice as commonly as to their personal characteristics (e.g. sense of humour).

Are Approaches To Teaching And/or Student Evaluation Of Instruction Scores Related To The Amount Of Faculty Formal Eduational Co

The purpose of this study was to investigate if there are correlations among an instructor\u27s approach to teaching, student evaluation of instruction outcomes, and the amount of formal coursework in education a teacher has completed. Three research questions provided the focus for the study: (1) to determine if there is a correlation between the number of formal educational courses taken by athletic training educational program (ATEP) faculty and their approach to teaching; (2) to determine if there is a correlation between the amount of formal educational courses taken by ATEP faculty and their students\u27 evaluations of instruction; and (3) to determine if there is a relationship between faculty\u27s approach to teaching and students\u27 evaluations of instruction. The population for the study was certified athletic trainers working as full-time faculty in ATEPs in the State of Florida. Data were generated using all eligible faculty from 10 of the 13 universities in Florida that offer Athletic Training Educational Programs. The study included faculty who teach in large and small ATEPs. Faculty from public and private, large and small universities were also represented. The faculty completed questionnaires that included demographic information, the Approaches to Teaching Inventory (ATI-R) and the Students\u27 Evaluation of Educational Quality (SEEQ) questionnaire. Based on the research findings, there is clear evidence that there is a lack of uniformity among ATEP faculty in the area of formal exposure to pedagogy and curriculum. 17.6% (n = 3) of respondents earned a bachelor\u27s degree in physical education and 18.8% (n = 3) of respondents earned a master\u27s degree in education, health education, or physical education. Of the 77.8% (n = 14) of respondents who completed or were in progress with a doctoral degree, 42.9% (n = 6) degrees were related to education. Faculty reported completing a mean of 9.25 courses related to education (SD = 7.39). The number of educational courses taken ranged from 0 to 25 courses. The study demonstrates that there is a correlation of large effect size between the amount of formal educational coursework and the SEEQ subscale value of Assignments/Readings. In addition, the Assignments/Readings and Learning/Academic Value subscale scores on the SEEQ were significantly higher when instructors had completed more than 10 educational courses. The study found moderate and large correlations and medium and large effect sizes between the scores of 7 of the 8 remaining SEEQ subscales and the number of education courses taken by faculty. In addition, there was a moderate correlation and medium effect size between the total score of the SEEQ and the number of education courses taken by faculty. Though statistically non-significant, each of these correlations were positive and may demonstrate a need for the study to be replicated using greater statistical power

Do instructional attributes pose multicollinearity problems? An empirical exploration

It is commonly perceived that variables ‘measuring’ different dimensions of teaching (construed as instructional attributes) used in student evaluation of teaching (SET) questionnaires are so highly correlated that they pose a serious multicollinearity problem for quantitative analysis including regression analysis. Using nearly 12000 individual student responses to SET questionnaires and ten key dimensions of teaching and 25 courses at various undergraduate and postgraduate levels for multiple years at a large Australian university, this paper investigates whether this is indeed the case and if so under what circumstances. This paper tests this proposition first by examining variance inflation factors (VIFs), across courses, levels and over time using individual responses; and secondly by using class averages. In the first instance, the paper finds no sustainable evidence of multicollinearity. While, there were one or two isolated cases of VIFs marginally exceeding the conservative threshold of 5, in no cases did the VIFs for any of the instructional attributes come anywhere close to the high threshold value of 10. In the second instance, however, the paper finds that the attributes are highly correlated as all the VIFs exceed 10. These findings have two implications: (a) given the ordinal nature of the data ordered probit analysis using individual student responses can be employed to quantify the impact of instructional attributes on TEVAL score; (b) Data based on class averages cannot be used for probit analysis. An illustrative exercise using level 2 undergraduate courses data suggests higher TEVAL scores depend first and foremost on improving explanation, presentation, and organization of lecture materials.Multicollinearity, variance inflation factor, instructional attributes, threshold, Australia